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Response Letter to Koivisto et al. 'Evaluating the Theoretical Background of STOFFENMANAGER® and the Advanced REACH Tool'

  • Wouter Fransman*
  • , Mario Arnone
  • , Francesca Borghi
  • , Andrea Cattaneo
  • , Domenico M. Cavallo
  • , John W. Cherrie
  • , Remy Franken
  • , Karen S. Galea
  • , Rudolf Van Der Haar
  • , Gerardus A.H. Heussen
  • , Keld Alstrup Jensen
  • , Milja Koponen
  • , Dorothea Koppisch
  • , Hans Kromhout
  • , Yu Syuan Luo
  • , Kevin McNally
  • , Arto Säämänen
  • , Andrea Spinazzè
  • , Martie Van Tongeren
  • , Jeroen Vanoirbeek
  • Steven Verpaele, Daniel Vetter, Susana Viegas, Nick Warren
*Corresponding author for this work
  • Netherlands Organisation for Applied Scientific Research (TNO)
  • Institute for Occupational Safety and Health of the German Social Accident Insurance (IFA)
  • University of Insubria
  • Institute of Occupational Medicine (IOM)
  • Heriot-Watt University
  • Mutual Insurance Society for Accidents at Work and Occupational Diseases MC MUTUAL
  • Cosanta B.V.
  • National Research Centre for the Working Environment (NFA)
  • Finnish Institute of Occupational Health (FIOH)
  • Utrecht University
  • National Taiwan University
  • Health and Safety Laboratory
  • University of Manchester
  • Katholieke Universiteit Leuven (KU Leuven)
  • Nickel Institute (Belgium)
  • EBRC Consulting GmbH
  • Universidade Nova de Lisboa

Research output: Contribution to journalArticleScientificpeer-review

Abstract

In this article, we have responded to the key statements in the article by Koivisto et al. (2022) that were incorrect and considered to be a biased critique on a subset of the exposure models used in Europe (i.e. ART and Stoffenmanager®) used for regulatory exposure assessment. We welcome scientific discussions on exposure modelling (as was done during the ISES Europe workshop) and criticism based on scientific evidence to contribute to the advancement of occupational exposure estimation tools. The tiered approach to risk assessment allows various exposure assessment models from screening tools (control/hazard banding) through to higher-tiered approaches. There is a place for every type of model, but we do need to recognize the cost and data requirements of highly bespoke assessments. That is why model developers have taken pragmatic approaches to develop tools for exposure assessments based on imperfect data. We encourage Koivisto et al. to focus on further scientifically robust work to develop mass-balance models and by independent external validations studies, compare these models with alternative model tools such as ART and Stoffenmanager®.

Original languageEnglish
Pages (from-to)543-549
JournalAnnals of Work Exposures and Health
Volume66
Issue number4
DOIs
Publication statusPublished - 1 May 2022
MoE publication typeA1 Journal article-refereed

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • exposure assessment
  • exposure estimation
  • exposure modelling
  • regulation of chemicals
  • regulatory risk assessment
  • SMEs
  • Risk Assessment
  • Europe
  • Humans
  • Occupational Exposure

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